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Jak w nasyconym kanale HoReCa podejmować decyzje inwestycyjne, które konsekwentnie budują przewagę rynkową? To strategiczne wyzwanie, przed którym stanął nasz partner, Grupa Żywiec, zarządzając siecią dystrybucji w 9 000 lokalach w całej Polsce.🎯

Tradycyjne modele oceny, oparte na wewnętrznych danych i subiektywnych ocenach, nie oddają już pełni potencjału. Naszą rolą było dostarczenie twardych danych z zewnątrz, które pokazują, co naprawdę dzieje się wokół każdego punktu.

W ramach naszego rozwiązania Source, zasililiśmy trójfilarowy model scoringowy Grupa Żywiec precyzyjnym zestawem danych geoprzestrzennych, w tym:

➡️ Średnim dziennym natężeniem ruchu pieszego i jego dynamiką.
➡️ Wskaźnikiem osób zatrzymujących się w bezpośredniej okolicy.
➡️ Cyfrową reputacją lokalu (ocenami i liczbą opinii Google).

Efekt? Teraz każda decyzja o inwestycji czy działaniach trade marketingowych opiera się na obiektywnym, ustandaryzowanym scoringu. To doskonały przykład, jak analityka geoprzestrzenna staje się kluczowym elementem strategii w branży FMCG.

Jesteśmy dumni, że możemy być partnerem w tak strategicznym projekcie. Gratulacje dla całego zespołu Grupa Żywiec za odważne, innowacyjne podejście! 🚀

Chcesz dowiedzieć się więcej? Poznaj pełne case study ➡️
https://dataplace.ai/pl/success-stories/zywiec-segmentacja-punktow-gastronomicznych/

How easy is it to estimate the number of customers your point of sale will attract? 👥 🔍

Several seconds! Our web app calculate customer attraction forecast and shows what percentage of them will choose a particular POS. 💰

Only 3 simple steps keep you from this knowledge.

1️⃣ Specify the catchment area you want to analyse. It means the distance from which clients can come to visit your POS, for instance: 2 km by bike, 10 minutes on foot, 5 minutes by car etc.

2️⃣ Choose which category of POS out of the 8 available is your competition – grocery stores, pharmacies or maybe restaurants?

3️⃣ Click the button „Apply” and our app will prepare ready-made analyses for your business.

Click on the link and register to our app and use this option for free!
👉 https://lnkd.in/e3-Xxb9N

The model is based on the following factors, among others:

💡 Number of residents registered in the analysed area
💡 The presence of competitive points
💡 Distance from the place of residence to the point of sale and service

Be aware what number of residents might choose a particular location as a place of purchase.

DM drugstore enters Poland! We checked if their first location was surely a wise choice! 🎯

German drugstore chain dm-drogerie markt Deutschland is launching first outlet on the Polish market. Its first store will appear in Galaktyka Park shopping center in . DM targets people who appreciate affordable prices and a wide range of products. What are the key features of this area? Will the company find a target group? 🤔

Our analyses have shown that around 76,000 people pass by the building every day, but only 31% of them are permanent residents within a 10-minute walk from the shopping center. 🏘

The demographic profile shows that elderly people (above 65 y.o) represent 25.5% of the population, but the average age is 37 years. Women make up 58.4% of residents compared to 41.6% of men.

Expenditure on the items offered in the DM product range amounts to: Hygiene and Beauty 123 PLN (27 Euro) per capita and a total of 444 692 PLN per month (98 785 Euro). For products needed to maintain the home, the average resident spends 64 PLN per month (14 Euro), which amounts to 230 740 (51 257 Euro).💸 💸

Average earnings within 10-min walk from the Galaktyka Park is 3 760,11PLN netto (834,80 Euro). 84.8% city residents on average earn less than residents in the analysed location. 💰💰

According to analyses, within a 10-minute walking distance the DM will not have direct competition, which will certainly have a positive impact on customer capture and revenue.

It looks like DM has done their homework and analysed the location.

With our web app you can assess the potential of any location in terms of:
👉 How many people a day show up in front of any given point, and what percentage of them are locals versus visitors.
👉 Demographic profile of the area.
👉 How much do residents earn? How wealthy are they?
👉 What does the residents' receipt look like? What do they spend their money on?
👉 Shared traffic scan. How is the traffic shared between the different points?
👉 Distance and travel time. Is this point well-connected?
👉 What are planned or ongoing investments in the area?
👉 Popular hours. How is traffic distributed throughout the day?
👉 How is traffic distributed throughout the year? What are the characteristics of the traffic in the area?
👉 Where is the peak traffic in this area?
👉 Population Density. Heatmap visualizing the places with the largest population in the analysis area.

🔴 If you also want to start analyzing any location, try dataplace for a free trial now!